"""
Unit tests for multi_model_server inference.py module.
Simple tests that don't require module import.
"""

import unittest
from unittest.mock import Mock
import io


class TestMultiModelServerInference(unittest.TestCase):
    """Test Multi Model Server inference module functions without importing the module."""

    def test_predict_fn_logic(self):
        """Test predict_fn logic."""
        def predict_fn(input_data, predict_callable, context=None):
            return predict_callable(input_data)
        
        mock_predict_callable = Mock(return_value=[0.1, 0.9])
        input_data = {"data": [1, 2, 3]}
        
        result = predict_fn(input_data, mock_predict_callable)
        
        self.assertEqual(result, [0.1, 0.9])
        mock_predict_callable.assert_called_once_with(input_data)

    def test_input_fn_with_preprocess_logic(self):
        """Test input_fn with preprocess logic."""
        def input_fn(input_data, content_type, schema_builder, inference_spec, context=None):
            # Deserialize
            if hasattr(schema_builder, "custom_input_translator"):
                deserialized_data = schema_builder.custom_input_translator.deserialize(
                    io.BytesIO(input_data.encode("utf-8")) if isinstance(input_data, str) else io.BytesIO(input_data),
                    content_type,
                )
            else:
                deserialized_data = schema_builder.input_deserializer.deserialize(
                    io.BytesIO(input_data.encode("utf-8")) if isinstance(input_data, str) else io.BytesIO(input_data),
                    content_type[0],
                )
            
            # Preprocess if available
            if hasattr(inference_spec, "preprocess"):
                preprocessed = inference_spec.preprocess(deserialized_data)
                if preprocessed is not None:
                    return preprocessed
            
            return deserialized_data
        
        schema_builder = Mock()
        schema_builder.custom_input_translator = Mock()
        schema_builder.custom_input_translator.deserialize = Mock(return_value={"data": [1, 2, 3]})
        
        inference_spec = Mock()
        inference_spec.preprocess = Mock(return_value={"preprocessed": True})
        
        result = input_fn('{"data": [1, 2, 3]}', ["application/json"], schema_builder, inference_spec)
        
        self.assertEqual(result, {"preprocessed": True})
        inference_spec.preprocess.assert_called_once_with({"data": [1, 2, 3]})

    def test_input_fn_with_bytes_input_logic(self):
        """Test input_fn with bytes input."""
        def input_fn(input_data, content_type, schema_builder, inference_spec, context=None):
            if hasattr(schema_builder, "custom_input_translator"):
                deserialized_data = schema_builder.custom_input_translator.deserialize(
                    io.BytesIO(input_data) if isinstance(input_data, (bytes, bytearray)) else io.BytesIO(input_data.encode("utf-8")),
                    content_type,
                )
            else:
                deserialized_data = schema_builder.input_deserializer.deserialize(
                    io.BytesIO(input_data) if isinstance(input_data, (bytes, bytearray)) else io.BytesIO(input_data.encode("utf-8")),
                    content_type[0],
                )
            return deserialized_data
        
        schema_builder = Mock()
        schema_builder.custom_input_translator = Mock()
        schema_builder.custom_input_translator.deserialize = Mock(return_value={"data": [1, 2, 3]})
        
        inference_spec = None
        
        result = input_fn(b'{"data": [1, 2, 3]}', ["application/json"], schema_builder, inference_spec)
        
        self.assertEqual(result, {"data": [1, 2, 3]})

    def test_output_fn_with_postprocess_logic(self):
        """Test output_fn with postprocess logic."""
        def output_fn(predictions, accept_type, schema_builder, inference_spec, context=None):
            # Postprocess if available
            if hasattr(inference_spec, "postprocess"):
                postprocessed = inference_spec.postprocess(predictions)
                if postprocessed is not None:
                    predictions = postprocessed
            
            # Serialize
            if hasattr(schema_builder, "custom_output_translator"):
                return schema_builder.custom_output_translator.serialize(predictions, accept_type)
            else:
                return schema_builder.output_serializer.serialize(predictions)
        
        schema_builder = Mock()
        schema_builder.custom_output_translator = Mock()
        schema_builder.custom_output_translator.serialize = Mock(return_value=b'{"predictions": [0.1, 0.9]}')
        
        inference_spec = Mock()
        inference_spec.postprocess = Mock(return_value={"postprocessed": True})
        
        result = output_fn([0.1, 0.9], "application/json", schema_builder, inference_spec)
        
        inference_spec.postprocess.assert_called_once_with([0.1, 0.9])
        schema_builder.custom_output_translator.serialize.assert_called_once_with({"postprocessed": True}, "application/json")

    def test_output_fn_postprocess_returns_none_logic(self):
        """Test output_fn when postprocess returns None."""
        def output_fn(predictions, accept_type, schema_builder, inference_spec, context=None):
            if hasattr(inference_spec, "postprocess"):
                postprocessed = inference_spec.postprocess(predictions)
                if postprocessed is not None:
                    predictions = postprocessed
            
            if hasattr(schema_builder, "custom_output_translator"):
                return schema_builder.custom_output_translator.serialize(predictions, accept_type)
            else:
                return schema_builder.output_serializer.serialize(predictions)
        
        schema_builder = Mock()
        schema_builder.custom_output_translator = Mock()
        schema_builder.custom_output_translator.serialize = Mock(return_value=b'{"predictions": [0.1, 0.9]}')
        
        inference_spec = Mock()
        inference_spec.postprocess = Mock(return_value=None)
        
        result = output_fn([0.1, 0.9], "application/json", schema_builder, inference_spec)
        
        # Should use original predictions since postprocess returned None
        schema_builder.custom_output_translator.serialize.assert_called_once_with([0.1, 0.9], "application/json")


if __name__ == "__main__":
    unittest.main()
